Remove data labels and change data values to reduce bias in research!

Decades ago, physicists including Richard Feynman noticed something worrying. New estimates of basic physical constants were often closer to published values than would be expected given standard errors of measurement1. They realized that researchers were more likely to ‘confirm’ past results than refute them — results that did not conform to their expectation were more often systematically discarded or revised.

To minimize this problem, teams of particle physicists and cosmologists developed methods of blind analysis: temporarily and judiciously removing data labels and altering data values to fight bias and error. By the early 2000s, the technique had become widespread in areas of particle and nuclear physics.